Realize configurable QoS parameters of streaming video services
Simulate the streaming video lifecycle
Monitor the environment and quality data in system, terminal, and end user
Provide various objective evaluation algorithms and methods in real time
Provide subjective QoE evaluation metrics on customized aspects of user perception
Provide DASH easy-to-use DASH content generation and display tool
Provide all functional capabilities through a web based visual interface
Development of a data acquisition and analysis platform for video QoE: track video viewing experiences in real time
Development and evaluation of QoE metrics: supports multiple algorithms of objective video quality evaluation, and provides subjective QoE evaluations based on user opinions on customized video presentation
Development of a DASH enabled content generation tool and web client for video adaption
Terminal and End User: records terminal information, monitors user-viewing activities, and collects users’ ratings
Environment and Interface: the software framework and runtime environment for the user terminal
QoECenter Controller the target end-to-end video distribution flows from video source to end user terminal
QoECenter Core Modules three levels of parameter control, data acquisition, and data-driven analysis per the streaming video lifecycle
Cloud Resources a collection of scalable networking, compute, storage, and data resources
Video list recommendation
User data & user-viewing activities recoding
Ratings on customized aspects of user perception
A dash-enable web client allowing for adaptive bitrate streaming of video
Peak Signal to Noise Ratio (PSNR)
Structural Similarity Index Metric (SSIM)
Video Quality Measurement (VQM)
Source Analysis for Video Information
QoS Parameter Setting for Encoding and Network
DASH Content Generation Parameters & MPD Files
Objective Video Quality Evaluation & Subjective User Ratings
User and Terminal Information
Lingyan Zhang, Shangguang Wang, Fangchun Yang, Rong N. Chang. Qoecenter: A Visualized Platform for QoE Evaluation Of Streaming Video Services, IEEE ICWS 2017, research track, to appear.
Lingyan Zhang, Shangguang Wang*, Raymond K. Wong, Fangchun Yang, and Rong N. Chang. Cognitively Adjusting Imprecise User Preferences for Service Selection. IEEE Transactions on Network and Service Management, no.13, vol. 13, pp. 1-13.
Lingyan Zhang, Qibo Sun, Shangguang Wang, Sen Su, Fangchun Yang. Towards Video Quality of Experience and Selective Attention: A Subtitle-Based Measurement Study. IEEE SCC 2016, p. 872-875.
Lingyan Zhang, Mingzhe Yang, Yan Guo and Shangguang Wang, "Service selection and recommendation in integrated network environment", Book Chapter, IET Publisher, Stevenage, United Kingdom, 2017, ISBN: 978-1-78561-176-6. http://www.theiet.org/resources/books/telecom/Naas.cfm.
State Key Laboratory of Networking and Switching Technology
Beijing University of Posts and Telecommunications, China
“Research on Service Selection Mechanism in Integrated Network Environment”, Supported by the National Natural Science Foundation of China (Grant No. 61472047).
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